10559560 8323 Heinrich Peters 14954 Supervised Classification 18298 sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,columntransformer=sklearn.compose._column_transformer.ColumnTransformer(num=sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.StandardScaler),cat=sklearn.pipeline.Pipeline(onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)),svc=sklearn.svm.classes.SVC)(4) 8276172 copy true 17405 with_mean true 17405 with_std true 17405 add_indicator false 17407 copy true 17407 fill_value null 17407 missing_values NaN 17407 strategy "most_frequent" 17407 verbose 0 17407 categorical_features null 17408 categories null 17408 drop null 17408 dtype {"oml-python:serialized_object": "type", "value": "np.float64"} 17408 handle_unknown "ignore" 17408 n_values null 17408 sparse true 17408 C 1.0167588209539864 17495 cache_size 200 17495 class_weight null 17495 coef0 -0.6354734369237474 17495 decision_function_shape "ovr" 17495 degree 3 17495 gamma 0.0003345572257968965 17495 kernel "poly" 17495 max_iter -1 17495 probability true 17495 random_state 1 17495 shrinking true 17495 tol 0.001 17495 verbose false 17495 memory null 18298 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "simpleimputer", "step_name": "simpleimputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "columntransformer", "step_name": "columntransformer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "svc", "step_name": "svc"}}] 18298 verbose false 18298 n_jobs null 18299 remainder "drop" 18299 sparse_threshold 0.3 18299 transformer_weights null 18299 transformers [{"oml-python:serialized_object": "component_reference", "value": {"key": "num", "step_name": "num", "argument_1": [false, true, false, false, false, false, false, false, false, false, false, false, false, false, true, false, false, false, true, true, false, true, true, true, true, true, true, true, true, true, true, true, true, true, false, true, false]}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "cat", "step_name": "cat", "argument_1": [true, false, true, true, true, true, true, true, true, true, true, true, true, true, false, true, true, true, false, false, true, false, false, false, false, false, false, false, false, false, false, false, false, false, true, false, true]}}] 18299 verbose false 18299 memory null 18300 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "standardscaler", "step_name": "standardscaler"}}] 18300 verbose false 18300 memory null 18301 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "onehotencoder", "step_name": "onehotencoder"}}] 18301 verbose false 18301 openml-python Sklearn_0.21.2. 6332 cylinder-bands https://www.openml.org/data/download/1854224/phpAz9Len -1 22044107 description https://api.openml.org/data/download/22044107/description.xml -1 22044108 predictions https://api.openml.org/data/download/22044108/predictions.arff area_under_roc_curve 0.7700461088618983 [0.770046,0.770046] average_cost 0 f_measure 0.7149789928093471 [0.663755,0.752412] kappa 0.41617523167649534 kb_relative_information_score 0.22565377906005185 mean_absolute_error 0.3902979092172828 mean_prior_absolute_error 0.48794587945879536 weighted_recall 0.7148148148148148 [0.666667,0.75] number_of_instances 540 [228,312] precision 0.7151628486831854 [0.66087,0.754839] predictive_accuracy 0.7148148148148148 prior_entropy 0.9824743303740947 relative_absolute_error 0.7998795064120252 root_mean_prior_squared_error 0.49391365607219145 root_mean_squared_error 0.4373114231753799 root_relative_squared_error 0.8854005508838605 total_cost 0 unweighted_recall 0.7083333333333333 [0.666667,0.75] area_under_roc_curve 0.8316970546984572 [0.831697,0.831697] area_under_roc_curve 0.7980364656381488 [0.798036,0.798036] area_under_roc_curve 0.8134642356241234 [0.813464,0.813464] area_under_roc_curve 0.6921458625525948 [0.692146,0.692146] area_under_roc_curve 0.7741935483870968 [0.774194,0.774194] area_under_roc_curve 0.6690042075736327 [0.669004,0.669004] area_under_roc_curve 0.9158485273492287 [0.915849,0.915849] area_under_roc_curve 0.6423562412342216 [0.642356,0.642356] area_under_roc_curve 0.8352272727272727 [0.835227,0.835227] area_under_roc_curve 0.7457386363636362 [0.745739,0.745739] average_cost 0 average_cost 0 average_cost 0 average_cost 0 average_cost 0 average_cost 0 average_cost 0 average_cost 0 average_cost 0 average_cost 0 f_measure 0.7761994949494949 [0.727273,0.8125] f_measure 0.7388994107744108 [0.681818,0.78125] f_measure 0.705338441890166 [0.68,0.724138] f_measure 0.6666666666666666 [0.608696,0.709677] f_measure 0.7388994107744108 [0.681818,0.78125] f_measure 0.5751140048314796 [0.510638,0.622951] f_measure 0.8337402627601441 [0.808511,0.852459] f_measure 0.6470311581422692 [0.577778,0.698413] f_measure 0.7242568693562764 [0.680851,0.754098] f_measure 0.7407407407407407 [0.681818,0.78125] kappa 0.5404255319148936 kappa 0.46382978723404245 kappa 0.40740740740740744 kappa 0.3183730715287517 kappa 0.46382978723404245 kappa 0.13389121338912138 kappa 0.6610878661087867 kappa 0.27644569816643155 kappa 0.4367176634214186 kappa 0.4630681818181817 kb_relative_information_score 0.330596168361911 kb_relative_information_score 0.27434325243279356 kb_relative_information_score 0.28510210587128204 kb_relative_information_score 0.13281555598228958 kb_relative_information_score 0.2329273641732145 kb_relative_information_score 0.13392750465150105 kb_relative_information_score 0.33892056111741814 kb_relative_information_score 0.10533179912240068 kb_relative_information_score 0.25701569900825905 kb_relative_information_score 0.16531194523325052 mean_absolute_error 0.34202054700715767 mean_absolute_error 0.36890140172676233 mean_absolute_error 0.36059827051511123 mean_absolute_error 0.4303830140460883 mean_absolute_error 0.3903129223856458 mean_absolute_error 0.4273555292964495 mean_absolute_error 0.34684056748935965 mean_absolute_error 0.44386448341508344 mean_absolute_error 0.3746580356359214 mean_absolute_error 0.41804432065524755 mean_prior_absolute_error 0.48851988519885264 mean_prior_absolute_error 0.48851988519885264 mean_prior_absolute_error 0.48851988519885264 mean_prior_absolute_error 0.48851988519885264 mean_prior_absolute_error 0.48851988519885264 mean_prior_absolute_error 0.48851988519885264 mean_prior_absolute_error 0.48851988519885264 mean_prior_absolute_error 0.48851988519885264 mean_prior_absolute_error 0.4856498564985656 mean_prior_absolute_error 0.4856498564985656 number_of_instances 54 [23,31] number_of_instances 54 [23,31] number_of_instances 54 [23,31] number_of_instances 54 [23,31] number_of_instances 54 [23,31] number_of_instances 54 [23,31] number_of_instances 54 [23,31] number_of_instances 54 [23,31] number_of_instances 54 [22,32] number_of_instances 54 [22,32] precision 0.7768157768157766 [0.761905,0.787879] precision 0.7391374058040725 [0.714286,0.757576] precision 0.7146776406035665 [0.62963,0.777778] precision 0.6666666666666666 [0.608696,0.709677] precision 0.7391374058040725 [0.714286,0.757576] precision 0.5765432098765432 [0.5,0.633333] precision 0.8347222222222223 [0.791667,0.866667] precision 0.6463594276094277 [0.590909,0.6875] precision 0.730727969348659 [0.64,0.793103] precision 0.7407407407407407 [0.681818,0.78125] predictive_accuracy 0.7777777777777777 predictive_accuracy 0.7407407407407408 predictive_accuracy 0.7037037037037037 predictive_accuracy 0.6666666666666667 predictive_accuracy 0.7407407407407408 predictive_accuracy 0.5740740740740741 predictive_accuracy 0.8333333333333333 predictive_accuracy 0.6481481481481481 predictive_accuracy 0.7222222222222223 predictive_accuracy 0.7407407407407408 prior_entropy 0.9841440157771891 prior_entropy 0.9841440157771891 prior_entropy 0.9841440157771891 prior_entropy 0.9841440157771891 prior_entropy 0.9841440157771891 prior_entropy 0.9841440157771891 prior_entropy 0.9841440157771891 prior_entropy 0.9841440157771891 prior_entropy 0.9757955887617137 prior_entropy 0.9757955887617137 relative_absolute_error 0.7001159161984528 relative_absolute_error 0.7551410145292254 relative_absolute_error 0.7381445084232943 relative_absolute_error 0.8809938491467965 relative_absolute_error 0.7989703883328484 relative_absolute_error 0.8747965891347367 relative_absolute_error 0.7099824961028511 relative_absolute_error 0.9085904112877776 relative_absolute_error 0.7714571117906384 relative_absolute_error 0.8607936665919353 root_mean_prior_squared_error 0.49449439369385695 root_mean_prior_squared_error 0.49449439369385695 root_mean_prior_squared_error 0.49449439369385695 root_mean_prior_squared_error 0.49449439369385695 root_mean_prior_squared_error 0.49449439369385695 root_mean_prior_squared_error 0.49449439369385695 root_mean_prior_squared_error 0.49449439369385695 root_mean_prior_squared_error 0.49449439369385695 root_mean_prior_squared_error 0.4915838450298872 root_mean_prior_squared_error 0.4915838450298872 root_mean_squared_error 0.40275821201830736 root_mean_squared_error 0.42162783750582783 root_mean_squared_error 0.42247010543060537 root_mean_squared_error 0.46750564051374366 root_mean_squared_error 0.43402865264672197 root_mean_squared_error 0.475612025298374 root_mean_squared_error 0.3740594609468461 root_mean_squared_error 0.49585345292003397 root_mean_squared_error 0.41201758684907047 root_mean_squared_error 0.45304392159897355 root_relative_squared_error 0.8144848903335722 root_relative_squared_error 0.8526443229341422 root_relative_squared_error 0.8543476140846967 root_relative_squared_error 0.9454215183745397 root_relative_squared_error 0.877722089839163 root_relative_squared_error 0.9618147978292894 root_relative_squared_error 0.756448335344379 root_relative_squared_error 1.002748381465005 root_relative_squared_error 0.838143057414795 root_relative_squared_error 0.9216005085997679 total_cost 0 total_cost 0 total_cost 0 total_cost 0 total_cost 0 total_cost 0 total_cost 0 total_cost 0 total_cost 0 total_cost 0 unweighted_recall 0.7671809256661992 [0.695652,0.83871] unweighted_recall 0.729312762973352 [0.652174,0.806452] unweighted_recall 0.7082748948106592 [0.73913,0.677419] unweighted_recall 0.6591865357643759 [0.608696,0.709677] unweighted_recall 0.729312762973352 [0.652174,0.806452] unweighted_recall 0.5673211781206171 [0.521739,0.612903] unweighted_recall 0.832398316970547 [0.826087,0.83871] unweighted_recall 0.6374474053295933 [0.565217,0.709677] unweighted_recall 0.7230113636363636 [0.727273,0.71875] unweighted_recall 0.7315340909090908 [0.681818,0.78125] usercpu_time_millis 214.6819999999252 usercpu_time_millis 220.82000000000335 usercpu_time_millis 212.20800000003237 usercpu_time_millis 212.43999999995822 usercpu_time_millis 212.87600000005114 usercpu_time_millis 222.71200000000135 usercpu_time_millis 213.69999999996026 usercpu_time_millis 216.63800000004585 usercpu_time_millis 215.22999999996273 usercpu_time_millis 214.38200000000052 usercpu_time_millis_testing 9.577999999976328 usercpu_time_millis_testing 9.808000000020911 usercpu_time_millis_testing 9.536000000025524 usercpu_time_millis_testing 10.761999999999716 usercpu_time_millis_testing 9.490000000027976 usercpu_time_millis_testing 9.367999999994936 usercpu_time_millis_testing 9.68199999999797 usercpu_time_millis_testing 9.606000000019321 usercpu_time_millis_testing 9.493999999961034 usercpu_time_millis_testing 9.713999999974021 usercpu_time_millis_training 205.10399999994888 usercpu_time_millis_training 211.01199999998244 usercpu_time_millis_training 202.67200000000685 usercpu_time_millis_training 201.6779999999585 usercpu_time_millis_training 203.38600000002316 usercpu_time_millis_training 213.34400000000642 usercpu_time_millis_training 204.01799999996229 usercpu_time_millis_training 207.03200000002653 usercpu_time_millis_training 205.7360000000017 usercpu_time_millis_training 204.6680000000265 wall_clock_time_millis 107.84721374511719 wall_clock_time_millis 110.58497428894043 wall_clock_time_millis 106.27007484436035 wall_clock_time_millis 106.35614395141602 wall_clock_time_millis 106.66203498840332 wall_clock_time_millis 112.3819351196289 wall_clock_time_millis 107.38277435302734 wall_clock_time_millis 108.8097095489502 wall_clock_time_millis 107.90300369262695 wall_clock_time_millis 108.03890228271484 wall_clock_time_millis_testing 4.798173904418945 wall_clock_time_millis_testing 4.910945892333984 wall_clock_time_millis_testing 4.778861999511719 wall_clock_time_millis_testing 5.404949188232422 wall_clock_time_millis_testing 4.748106002807617 wall_clock_time_millis_testing 4.687070846557617 wall_clock_time_millis_testing 4.848718643188477 wall_clock_time_millis_testing 4.834890365600586 wall_clock_time_millis_testing 4.775047302246094 wall_clock_time_millis_testing 4.868745803833008 wall_clock_time_millis_training 103.04903984069824 wall_clock_time_millis_training 105.67402839660645 wall_clock_time_millis_training 101.49121284484863 wall_clock_time_millis_training 100.9511947631836 wall_clock_time_millis_training 101.9139289855957 wall_clock_time_millis_training 107.69486427307129 wall_clock_time_millis_training 102.53405570983887 wall_clock_time_millis_training 103.97481918334961 wall_clock_time_millis_training 103.12795639038086 wall_clock_time_millis_training 103.17015647888184 weighted_recall 0.7777777777777778 [0.695652,0.83871] weighted_recall 0.7407407407407407 [0.652174,0.806452] weighted_recall 0.7037037037037037 [0.73913,0.677419] weighted_recall 0.6666666666666666 [0.608696,0.709677] weighted_recall 0.7407407407407407 [0.652174,0.806452] weighted_recall 0.5740740740740741 [0.521739,0.612903] weighted_recall 0.8333333333333334 [0.826087,0.83871] weighted_recall 0.6481481481481481 [0.565217,0.709677] weighted_recall 0.7222222222222222 [0.727273,0.71875] weighted_recall 0.7407407407407407 [0.681818,0.78125]